Joseph Keshet
45 lines
1.2 KiB
Lua
45 lines
1.2 KiB
Lua
require 'torch' -- torch
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require 'optim'
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require 'rnn' -- provides a normalization operator
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function string:split(sep)
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local sep, fields = sep, {}
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local pattern = string.format("([^%s]+)", sep)
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self:gsub(pattern, function(substr) fields[#fields + 1] = substr end)
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return fields
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end
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local f_file = io.open(arg[1], 'r')
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local p_file = io.open(arg[2], 'w')
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local i = 0
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for line in f_file:lines('*l') do
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i = i + 1
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end
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local data = torch.Tensor(i, 351)
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i = 0
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local names = {}
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local line_counter = 0
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local f_file = io.open(arg[1], 'r')
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for line in f_file:lines('*l') do
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i = i+1
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line_counter = line_counter+1
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local l = line:split(',')
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first = true
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for key, val in ipairs(l) do
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if first == false then
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data[i][key] = val
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else data[i][key] = line_counter
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names[i] = val
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first = false
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end
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end
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end
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local X = data[{{},{2,-1}}]
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model = torch.load('tracking_model.dat')
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local myPrediction = model:forward(X)
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p_file:write('NAME,F1,F2,F3,F4\n')
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for p=1, (#myPrediction)[1] do
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p_file:write(names[p]..','..tostring(1000*myPrediction[p][1])..','..tostring(1000*myPrediction[p][2])..','..tostring(1000*myPrediction[p][3])..','..tostring(1000*myPrediction[p][4])..'\n')
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end
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